From past to future, mobility has been the heartbeat of life. Achieving seamless mobility will enable everyone to enjoy life more fully. However, as we strive to make this dream a reality, the complexity of systems increases, with AI playing a crucial role in bringing this vision closer. Beyond novel and complex functionalities, systems must ensure safe and secure operations. This new disruptive scenario, together with its enabler, AI engineering, introduces new challenges for safety engineering, making conventional approaches insufficient to guarantee safety. It is no longer enough to design a system, add safety features, and deploy it. Continuous monitoring, adjustments, development of the operational domain description, and further development are necessary. This underscores the importance of revisiting development and operational concepts to adapt to these evolving demands. In this session, you will:

• Learn about the new challenges AI introduces to safety engineering and why traditional methods are no longer sufficient.
• Discover the importance of ongoing monitoring, adjustments, and development to ensure safe and secure operations in AI-driven mobility systems.
• Explore “why” development of the operational domain description and its role is important for successful development and operation.

This stream focuses on the commercialization of autonomous vehicles and systems. Discover how Volvo’s integration of digital twins accelerates autonomous trucking development and reduces costs. Explore sensor fusion strategies for reliable performance in adverse weather conditions, and learn about the commercialization potential of transformer-based end-to-end stacks in real-world deployments. Additionally, understand the critical role of centralized computing architectures in scaling autonomous vehicle production and optimizing AI integration for market readiness.